Gastrointestinal(GI)cancers remain a leading cause of cancer-related morbidity and mortality worldwide.Artificial intelligence(AI),particularly machine learning and deep learning(DL),has shown promise in enhancing can...Gastrointestinal(GI)cancers remain a leading cause of cancer-related morbidity and mortality worldwide.Artificial intelligence(AI),particularly machine learning and deep learning(DL),has shown promise in enhancing cancer detection,diagnosis,and prognostication.A narrative review of literature published from January 2015 to march 2025 was conducted using PubMed,Web of Science,and Scopus.Search terms included"gastrointestinal cancer","artificial intelligence","machine learning","deep learning","radiomics","multimodal detection"and"predictive modeling".Studies were included if they focused on clinically relevant AI applications in GI oncology.AI algorithms for GI cancer detection have achieved high performance across imaging modalities,with endoscopic DL systems reporting accuracies of 85%-97%for polyp detection and segmentation.Radiomics-based models have predicted molecular biomarkers such as programmed cell death ligand 2 expression with area under the curves up to 0.92.Large language models applied to radiology reports demonstrated diagnostic accuracy comparable to junior radiologists(78.9%vs 80.0%),though without incremental value when combined with human interpretation.Multimodal AI approaches integrating imaging,pathology,and clinical data show emerging potential for precision oncology.AI in GI oncology has reached clinically relevant accuracy levels in multiple diagnostic tasks,with multimodal approaches and predictive biomarker modeling offering new opportunities for personalized care.However,broader validation,integration into clinical workflows,and attention to ethical,legal,and social implications remain critical for widespread adoption.展开更多
High-throughput transcriptomics has evolved from bulk RNA-seq to single-cell and spatial profiling,yet its clinical translation still depends on effective integration across diverse omics and data modalities.Emerging ...High-throughput transcriptomics has evolved from bulk RNA-seq to single-cell and spatial profiling,yet its clinical translation still depends on effective integration across diverse omics and data modalities.Emerging foundation models and multimodal learning frameworks are enabling scalable and transferable representations of cellular states,while advances in interpretability and real-world data integration are bridging the gap between discovery and clinical application.This paper outlines a concise roadmap for AI-driven,transcriptome-centered multi-omics integration in precision medicine(Figure 1).展开更多
Acute respiratory distress syndrome(ARDS)is a life-threatening condition that is characterized by high mortality rates and limited therapeutic options.Notably,Zhang et al demonstrated that CD146+mesenchymal stromal ce...Acute respiratory distress syndrome(ARDS)is a life-threatening condition that is characterized by high mortality rates and limited therapeutic options.Notably,Zhang et al demonstrated that CD146+mesenchymal stromal cells(MSCs)exhibited greater therapeutic efficacy than CD146-MSCs.These cells enhance epithelial repair through nuclear factor kappa B/cyclooxygenase-2-associated paracrine signaling and secretion of pro-angiogenic factors.We concur that MSCs hold significant promise for ARDS treatment;however,the heterogeneity of cell products is a translational barrier.Phenotype-aware strategies,such as CD146 enrichment,standardized potency assays,and extracellular vesicle profiling,are essential for improving the consistency of these studies.Further-more,advanced preclinical models,such as lung-on-a-chip systems,may provide more predictive insights into the therapeutic mechanisms.This article underscores the importance of CD146+MSCs in ARDS,emphasizes the need for precision in defining cell products,and discusses how integrating subset selection into translational pipelines could enhance the clinical impact of MSC-based therapies.展开更多
In the dynamic landscape of modern healthcare and precision medicine,the digital revolution is reshaping medical industries at an unprecedented pace,and traditional Chinese medicine(TCM)is no exception[1-4].The paper...In the dynamic landscape of modern healthcare and precision medicine,the digital revolution is reshaping medical industries at an unprecedented pace,and traditional Chinese medicine(TCM)is no exception[1-4].The paper“From digits towards digitization:the past,present,and future of traditional Chinese medicine”by Academician&TCM National Master Qi WANG(王琦).展开更多
In the era of precision medicine,the breast cancer surgical treatment field is gradually moving toward a de-escalation model.Through precise preoperative assessments and multidisciplinary decision-making,surgical trau...In the era of precision medicine,the breast cancer surgical treatment field is gradually moving toward a de-escalation model.Through precise preoperative assessments and multidisciplinary decision-making,surgical trauma can be decreased,and patients’quality of life can be improved by ensuring safety.Herein,we explore the axillary de-escalation surgery model for breast cancer.展开更多
Lynch syndrome(LS)is the most common hereditary colorectal cancer(CRC)predisposition syndrome,characterized by a high mutational burden and microsatellite instability-high(MSI-H)tumors.Immunology of LS-associated CRC(...Lynch syndrome(LS)is the most common hereditary colorectal cancer(CRC)predisposition syndrome,characterized by a high mutational burden and microsatellite instability-high(MSI-H)tumors.Immunology of LS-associated CRC(LS-CRC)is unique,with significant implications for treatment.Despite well-established knowledge of LS immunology,immunotherapy dose and treatment response can vary significantly based on local tumor immunity and specific germline pathogenic variant of LS genes.This variability necessitates tailored surveillance strategies and new personalised immunotherapy approaches for LS patients.LS-CRC often benefits from immunotherapy due to the distinct tumor microenvironment(TME)and the variety of tumor infiltrating lymphocytes(TILs).This perspective discusses a novel approach of analysing spatial TILs at a single-cell level using tumor whole slide images(WSIs)that accounts for the distinct TME of LS-CRC.By emphasizing the necessity of personalized medicine in hereditary cancer syndromes,the future research and clinical practices that enhance patient outcomes through precision oncology is inspired.展开更多
The management of breast cancer,one of the most common and heterogeneous malignancies,has transformed with the advent of precision medicine.This review explores current developments in genetic profiling,molecular diag...The management of breast cancer,one of the most common and heterogeneous malignancies,has transformed with the advent of precision medicine.This review explores current developments in genetic profiling,molecular diagnostics,and targeted therapies that have revolutionized breast cancer treatment.Key innovations,such as cyclin-dependent kinases 4/6(CDK4/6)inhibitors,antibodydrug conjugates(ADCs),and immune checkpoint inhibitors(ICIs),have improved outcomes for hormone receptor-positive(HR+),HER2-positive(HER2+),and triple-negative breast cancer(TNBC)subtypes remarkably.Additionally,emerging treatments,such as PI3K inhibitors,poly(ADP-ribose)polymerase(PARP)inhibitors,and m RNA-based therapies,offer new avenues for targeting specific genetic mutations and improving treatment response,particularly in difficult-to-treat breast cancer subtypes.The integration of liquid biopsy technologies provides a non-invasive approach for real-time monitoring of tumor evolution and treatment response,thus enabling dynamic adjustments to therapy.Molecular imaging and artificial intelligence(AI)are increasingly crucial in enhancing diagnostic precision,personalizing treatment plans,and predicting therapeutic outcomes.As precision medicine continues to evolve,it has the potential to significantly improve survival rates,decrease recurrence,and enhance quality of life for patients with breast cancer.By combining cutting-edge diagnostics,personalized therapies,and emerging treatments,precision medicine can transform breast cancer care by offering more effective,individualized,and less invasive treatment options.展开更多
Artificial intelligence(AI)is driving a paradigm shift in gastroenterology and hepa-tology by delivering cutting-edge tools for disease screening,diagnosis,treatment,and prognostic management.Through deep learning,rad...Artificial intelligence(AI)is driving a paradigm shift in gastroenterology and hepa-tology by delivering cutting-edge tools for disease screening,diagnosis,treatment,and prognostic management.Through deep learning,radiomics,and multimodal data integration,AI has achieved diagnostic parity with expert cli-nicians in endoscopic image analysis(e.g.,early gastric cancer detection,colorectal polyp identification)and non-invasive assessment of liver pathologies(e.g.,fibrosis staging,fatty liver typing)while demonstrating utility in personalized care scenarios such as predicting hepatocellular carcinoma recurrence and opti-mizing inflammatory bowel disease treatment responses.Despite these advance-ments challenges persist including limited model generalization due to frag-mented datasets,algorithmic limitations in rare conditions(e.g.,pediatric liver diseases)caused by insufficient training data,and unresolved ethical issues related to bias,accountability,and patient privacy.Mitigation strategies involve constructing standardized multicenter databases,validating AI tools through prospective trials,leveraging federated learning to address data scarcity,and de-veloping interpretable systems(e.g.,attention heatmap visualization)to enhance clinical trust.Integrating generative AI,digital twin technologies,and establishing unified ethical/regulatory frameworks will accelerate AI adoption in primary care and foster equitable healthcare access while interdisciplinary collaboration and evidence-based implementation remain critical for realizing AI’s potential to redefine precision care for digestive disorders,improve global health outcomes,and reshape healthcare equity.展开更多
Organoids are three-dimensional stem cell-derived models that offer a more physiologically relevant representation of tumor biology compared to traditional two-dimensional cell cultures or animal models.Organoids pres...Organoids are three-dimensional stem cell-derived models that offer a more physiologically relevant representation of tumor biology compared to traditional two-dimensional cell cultures or animal models.Organoids preserve the complex tissue architecture and cellular diversity of human cancers,enabling more accurate predictions of tumor growth,metastasis,and drug responses.Integration with microfluidic platforms,such as organ-on-a-chip systems,further enhances the ability to model tumor-environment interactions in real-time.Organoids facilitate in-depth exploration of tumor heterogeneity,molecular mechanisms,and the development of personalized treatment strategies when coupled with multi-omics technologies.Organoids provide a platform for investigating tumor-immune cell interactions,which aid in the design and testing of immune-based therapies and vaccines.Taken together,these features position organoids as a transformative tool in advancing cancer research and precision medicine.展开更多
Artificial intelligence(AI)and machine learning(ML)are transforming spine care by addressing diagnostics,treatment planning,and rehabilitation challenges.This study highlights advancements in precision medicine for sp...Artificial intelligence(AI)and machine learning(ML)are transforming spine care by addressing diagnostics,treatment planning,and rehabilitation challenges.This study highlights advancements in precision medicine for spinal pathologies,leveraging AI and ML to enhance diagnostic accuracy through deep learning algorithms,enabling faster and more accurate detection of abnormalities.AIpowered robotics and surgical navigation systems improve implant placement precision and reduce complications in complex spine surgeries.Wearable devices and virtual platforms,designed with AI,offer personalized,adaptive therapies that improve treatment adherence and recovery outcomes.AI also enables preventive interventions by assessing spine condition risks early.Despite progress,challenges remain,including limited healthcare datasets,algorithmic biases,ethical concerns,and integration into existing systems.Interdisciplinary collaboration and explainable AI frameworks are essential to unlock AI’s full potential in spine care.Future developments include multimodal AI systems integrating imaging,clinical,and genetic data for holistic treatment approaches.AI and ML promise significant improvements in diagnostic accuracy,treatment personalization,service accessibility,and cost efficiency,paving the way for more streamlined and effective spine care,ultimately enhancing patient outcomes.展开更多
The gears of new energy vehicles are required to withstand higher rotational speeds and greater loads,which puts forward higher precision essentials for gear manufacturing.However,machining process parameters can caus...The gears of new energy vehicles are required to withstand higher rotational speeds and greater loads,which puts forward higher precision essentials for gear manufacturing.However,machining process parameters can cause changes in cutting force/heat,resulting in affecting gear machining precision.Therefore,this paper studies the effect of different process parameters on gear machining precision.A multi-objective optimization model is established for the relationship between process parameters and tooth surface deviations,tooth profile deviations,and tooth lead deviations through the cutting speed,feed rate,and cutting depth of the worm wheel gear grinding machine.The response surface method(RSM)is used for experimental design,and the corresponding experimental results and optimal process parameters are obtained.Subsequently,gray relational analysis-principal component analysis(GRA-PCA),particle swarm optimization(PSO),and genetic algorithm-particle swarm optimization(GA-PSO)methods are used to analyze the experimental results and obtain different optimal process parameters.The results show that optimal process parameters obtained by the GRA-PCA,PSO,and GA-PSO methods improve the gear machining precision.Moreover,the gear machining precision obtained by GA-PSO is superior to other methods.展开更多
Approximately 2.5%of the global population experience allergic reactions to seafood,making it one of the most prevalent and life-threatening allergies.Seafood allergy can lead to the disruption of the intestinal barri...Approximately 2.5%of the global population experience allergic reactions to seafood,making it one of the most prevalent and life-threatening allergies.Seafood allergy can lead to the disruption of the intestinal barrier,possibly due to aberrant intestinal glycosylation.In this study,the mechanisms underlying seafood allergy were explored through the lens of intestinal glycobiology.Mice were sensitized with tropomyosin,resulting in significant increases in allergy symptom scores,specific antibody and T helper 2 cytokine levels.Intestinal damage was confirmed by histopathology,as well as by assessments and levels of diamine oxidase and claudin-1.Moreover,alterations in glycosylated proteins within the jejunum were analyzed using highthroughput mass spectrometry and the pGlyco3.0 search engine.Precision N-glycoproteomics analysis yielded 2283 glycosylation peptides corresponding to 655 unique glycosylation sites on 399 proteins.Differential expression and enrichment analyses revealed that differentially expressed glycoproteins were significantly enriched in the extracellular matrix(ECM)-receptor interaction pathway and focal adhesion pathway.In conclusion,tropomyosin sensitization leads to intestinal glycome changes,accompanied by remodeling of the intestinal ECM.Our research establishes an essential theoretical basis for targeting the intestinal glycome and ECM remodeling in a precise and fine-tuned manner for the treatment of food allergies.展开更多
Background:Precision medicine(PM)has taken center stage in healthcare since the completion of the genomic project.Developed countries have gradually integrated PM into mainstream patient management.However,Nigeria sti...Background:Precision medicine(PM)has taken center stage in healthcare since the completion of the genomic project.Developed countries have gradually integrated PM into mainstream patient management.However,Nigeria still grapples with wide acceptance,key translational research and implementation of PM.This study sought to explore the knowledge and attitude of PM among pharmacists as key stakeholders in the healthcare team.Methods:A cross‐sectional study was conducted in selected tertiary hospitals across the country.A 21‐item semi‐structured questionnaire was administered by hybrid online and physical methods and the results analyzed with Statistical Package for the Social Sciences Version 25.Descriptive statistics were used to summarize the data.A chi‐square test was employed to determine the association of knowledge of PM and the sociodemographic characteristics of the study population.Results:A total of 167 hospital pharmacists participated in the study.A high proportion of the participants are familiar with artificial intelligence(91.75%),Pharmacogenomics(84.5%),and precision medicine(61%).Overall,38.9%of the pharmacists had a good knowledge while 13.2%had a poor knowledge of PM and associated terms.The level of knowledge did not correlate significantly with gender(X^(2)=3.21,p=0.201),age(X^(2)=5,p=0.27),marital status(X^(2)=3.21,p=0.201),and professional level(X^(2)=6.85,p=0.144).The most important value of precision medicine to hospital pharmacists is the ability to minimize the impact of disease through preventive medicine(49%)while a large portion are pursuing and or actively planning to pursue additional education in precision medicine.Conclusions:There is a highly positive attitude toward the prospect of PM among hospital pharmacists in Nigeria.Education modules in this field are highly recommended as most do not have a holistic knowledge of terms used in PM.Also,more research aimed at translating PM knowledge into clinical practice is recommended.展开更多
Pancreatic ductal adenocarcinoma(PDAC)is a global health challenge and remains one of the most lethal malignancies;there are only a few therapeutic options.However,significant efforts have led to the identification of...Pancreatic ductal adenocarcinoma(PDAC)is a global health challenge and remains one of the most lethal malignancies;there are only a few therapeutic options.However,significant efforts have led to the identification of major genetic factors that drive the progression and pathogenesis of PDAC.Notably,the research and application of molecular targeted therapies and immunotherapies have rapidly increased and facilitated great progress in the treatment of many malignant tumors,additional targeted therapies and immunotherapy based on next-generation sequencing results provide new opportunities for the diagnosis and treatment of pancreatic tumors.Immune checkpoint inhibitors are also now being incorporated as PDAC therapies,and combinations of molecularly targeted therapies with immunotherapies are emerging as strategies for boosting the immune response.The investigation of biomarkers of a response or primary resistance to immunotherapies is also an emerging research area.Herein,we further discuss the recent technological advances that continue to expand our understanding of PDAC complexity.We discuss the advancements expected in the near future,including biomarker-driven treatments and immunotherapies.We presume that the clinical translation of these research efforts will improve the survival outcomes of this challenging disease,which are currently dismal.展开更多
Micro-grinding has been widely used in aerospace and other industry.However,the small diameter of the micro-grinding tool has limited its machining performance and efficiency.In order to solve the above problems,micro...Micro-grinding has been widely used in aerospace and other industry.However,the small diameter of the micro-grinding tool has limited its machining performance and efficiency.In order to solve the above problems,micro-structure has been applied on the micro-grinding tool.A morphology modeling has been established in this study to characterize the surface of microstructured micro-grinding tool,and the grinding performance of micro-structured micro-grinding tool has been analyzed through undeformed chip thickness,abrasive edge width,and effective distance between abrasives.Then deviation analysis,path optimization and parameter optimization of microchannel array precision grinding have been finished to improve processing quality and efficiency,and the deflection angle has the most obvious effects on the rectangular slot depth,micro-structured micro-grinding tool could reduce 10%surface roughness and 20%grinding force compared to original micro-grinding tool.Finally,the microchannel array has been machined with a size deviation of 2μm and surface roughness of 0.2μm.展开更多
With the rapid development of artificial intelligence(AI)technology,multimodal data integration has become an important means to improve the accuracy of diagnosis and treatment in gastroenterology and hepatology.This ...With the rapid development of artificial intelligence(AI)technology,multimodal data integration has become an important means to improve the accuracy of diagnosis and treatment in gastroenterology and hepatology.This article systematically reviews the latest progress of multimodal AI technology in the diagnosis,treatment,and decision-making for gastrointestinal tumors,functional gastrointestinal diseases,and liver diseases,focusing on the innovative applications of endoscopic image AI,pathological section AI,multi-omics data fusion models,and wearable devices combined with natural language processing.Multimodal AI can significantly improve the accuracy of early diagnosis and the efficiency of individualized treatment planning by integrating imaging,pathological data,molecular,and clinical phenotypic data.However,current AI technologies still face challenges such as insufficient data standardization,limited generalization of models,and ethical compliance.This paper proposes solutions,such as the establishment of cross-center data sharing platform,the development of federated learning framework,and the formulation of ethical norms,and looks forward to the application prospect of multimodal large-scale models in the disease management process.This review provides theoretical basis and practical guidance for promoting the clinical translation of AI technology in the field of gastroenterology and hepatology.展开更多
Colorectal cancer(CRC)ranks as the third most common cancer globally and the second leading cause of cancer-related deaths,representing a significant health burden.Despite advancements in traditional treatments such a...Colorectal cancer(CRC)ranks as the third most common cancer globally and the second leading cause of cancer-related deaths,representing a significant health burden.Despite advancements in traditional treatments such as surgery,chemotherapy,targeted therapy,and immunotherapy,these approaches still face challenges,including high costs,limited efficacy,and drug resistance.Drug repurposing has emerged as a promising strategy for CRC treatment,offering advantages with reduced development timelines,lower costs,and improved drug accessibility.This review explores drug repurposing strategies for CRC,supported by multidisciplinary technologies,and discusses the current challenges in the field.展开更多
The increasing use of UAV-based LiDAR systems for high-resolution mapping highlights the need for reliable,field-validated accuracy assessment methods.This study presents a practical technique for evaluating geometric...The increasing use of UAV-based LiDAR systems for high-resolution mapping highlights the need for reliable,field-validated accuracy assessment methods.This study presents a practical technique for evaluating geometric and radiometric performance using georeferenced,high-reflectivity foil targets.The method enables precise extraction of target centers and correction of systematic georeferencing errors through 3D transformation.The approach was applied at the Tora Cement Factory in Cairo,Egypt—an industrial site with complex topography—using a DJI Matrice 300 RTK UAV equipped with the Zenmuse L1 LiDAR sensor and Zenmuse P1 photogrammetric camera.Three test flights were performed at altitudes of 50 m(nadir and oblique)and 70 m(oblique),with a high-resolution Structure-from-Motion(SfM)point cloud generated for reference.After transformation,the global RMSE of the LiDAR dataset was reduced to approximately 2.8∼3.2 cm,improving upon the raw uncorrected accuracy of up to 4.6 cm.Surface-wise comparisons showed RMSEs of 3.1 cm on flat areas,3.8 cm on rugged terrain,and 4.5 cm on vertical structures.Additionally,the RGB data embedded in the LiDAR point cloud exhibited a systematic spatial offset between 18 and 43 cm,with an average internal standard deviation near 5 cm,indicating a potential limitation for radiometric applications.The proposed method offers a cost-effective,accurate,and repeatable solution for UAV LiDAR validation and supports operational deployment,quality assurance,and system calibration in real-world scenarios.展开更多
Assembly precision greatly influences the performance of complex high-end equipment.The traditional industrial assembly process and deviation transfer are implicit and uncertain,causing problems like poor component fi...Assembly precision greatly influences the performance of complex high-end equipment.The traditional industrial assembly process and deviation transfer are implicit and uncertain,causing problems like poor component fit and hard-to-trace assembly stress concentration.Assemblers can only check whether the dimensional tolerance of the component design is exceeded step by step in combination with prior knowledge.Inversion in industrial assembly optimizes assembly and design by comparing real and theoretical results and doing inversion analysis to reduce assembly deviation.The digital twin(DT)technology visualizes and predicts the assembly process by mapping real and virtual model parameters and states simultaneously,expanding parameter range for inversion analysis and improving inversion result accuracy.Problems in improving industrial assembly precision and the significance and research status of DT-driven parametric inversion of assembly tools,processes and object precision are summarized.It analyzes vital technologies for assembly precision inversion such as multi-attribute assembly process parameter sensing,virtual modeling of high-fidelity assembly systems,twin synchronization of assembly process data models,multi-physical field simulation,and performance twin model construction of the assembly process.Combined with human-cyber-physical system,augmented reality,and generative intelligence,the outlook of DT-driven assembly precision inversion is proposed,providing support for DT's use in industrial assembly and precision improvement.展开更多
Colon-targeted oral drug delivery systems are one of the most promising therapeutic strategies for alleviating and curing inflammatory bowel disease(IBD),but they still face challenges in successfully passing through ...Colon-targeted oral drug delivery systems are one of the most promising therapeutic strategies for alleviating and curing inflammatory bowel disease(IBD),but they still face challenges in successfully passing through the harsh gastrointestinal environment and intestinal mucus barrier.To overcome the gastrointestinal barriers for oral drug delivery mentioned above,a“spore-like”oral nanodrug delivery platform(Cur/COS/SC NPs)has been developed.Firstly,chitooligosaccharides(COS)are encapsulated on the surface of Curcumin nanoparticles(Cur NPs)to form carrier-free nanoparticles(Cur/COS NPs).Subsequently,inspired by the natural high resistance of spore coat(SC),SC is chosen as the“protective umbrella”to encapsulate Cur/COS NPs for precision targeted therapy of IBD.After oral administration,SC can effectively protect NPs through the rugged gastrointestinal environment and exhibit excellent intestinal mucus penetration characteristics.Moreover,the negatively-charged Cur/COS/SC NPs specifically target positivelycharged inflamed colon via electrostatic interactions.It is demonstrated that Cur/COS/SC NPs can promote the expression of tight junction proteins,inhibit aberrant activation of the Toll-like receptor 4/myeloid differentiation primary response gene 88/nuclear factor-κB(TLR4/MyD88/NF-κB)signaling pathway,and downregulate the levels of pro-inflammatory factors,exhibiting excellent anti-inflammatory effects.Notably,it is found that Cur/COS/SC NPs can significantly increase the richness and diversity of gut microbiota,and restore the homeostasis of gut microbiota by inhibiting pathogenic bacteria and promoting probiotics.Hence,Cur/COS/SC NPs provide a safe,efficient,and feasible new strategy for IBD treatment.展开更多
文摘Gastrointestinal(GI)cancers remain a leading cause of cancer-related morbidity and mortality worldwide.Artificial intelligence(AI),particularly machine learning and deep learning(DL),has shown promise in enhancing cancer detection,diagnosis,and prognostication.A narrative review of literature published from January 2015 to march 2025 was conducted using PubMed,Web of Science,and Scopus.Search terms included"gastrointestinal cancer","artificial intelligence","machine learning","deep learning","radiomics","multimodal detection"and"predictive modeling".Studies were included if they focused on clinically relevant AI applications in GI oncology.AI algorithms for GI cancer detection have achieved high performance across imaging modalities,with endoscopic DL systems reporting accuracies of 85%-97%for polyp detection and segmentation.Radiomics-based models have predicted molecular biomarkers such as programmed cell death ligand 2 expression with area under the curves up to 0.92.Large language models applied to radiology reports demonstrated diagnostic accuracy comparable to junior radiologists(78.9%vs 80.0%),though without incremental value when combined with human interpretation.Multimodal AI approaches integrating imaging,pathology,and clinical data show emerging potential for precision oncology.AI in GI oncology has reached clinically relevant accuracy levels in multiple diagnostic tasks,with multimodal approaches and predictive biomarker modeling offering new opportunities for personalized care.However,broader validation,integration into clinical workflows,and attention to ethical,legal,and social implications remain critical for widespread adoption.
文摘High-throughput transcriptomics has evolved from bulk RNA-seq to single-cell and spatial profiling,yet its clinical translation still depends on effective integration across diverse omics and data modalities.Emerging foundation models and multimodal learning frameworks are enabling scalable and transferable representations of cellular states,while advances in interpretability and real-world data integration are bridging the gap between discovery and clinical application.This paper outlines a concise roadmap for AI-driven,transcriptome-centered multi-omics integration in precision medicine(Figure 1).
基金the Scientific and Technological Research Council of Türkiye(TÜBİTAK)Under the International Postdoctoral Research Fellowship Program(2219),No.1059B192400980the National Postdoctoral Research Fellowship Program(2218),No.122C158.
文摘Acute respiratory distress syndrome(ARDS)is a life-threatening condition that is characterized by high mortality rates and limited therapeutic options.Notably,Zhang et al demonstrated that CD146+mesenchymal stromal cells(MSCs)exhibited greater therapeutic efficacy than CD146-MSCs.These cells enhance epithelial repair through nuclear factor kappa B/cyclooxygenase-2-associated paracrine signaling and secretion of pro-angiogenic factors.We concur that MSCs hold significant promise for ARDS treatment;however,the heterogeneity of cell products is a translational barrier.Phenotype-aware strategies,such as CD146 enrichment,standardized potency assays,and extracellular vesicle profiling,are essential for improving the consistency of these studies.Further-more,advanced preclinical models,such as lung-on-a-chip systems,may provide more predictive insights into the therapeutic mechanisms.This article underscores the importance of CD146+MSCs in ARDS,emphasizes the need for precision in defining cell products,and discusses how integrating subset selection into translational pipelines could enhance the clinical impact of MSC-based therapies.
文摘In the dynamic landscape of modern healthcare and precision medicine,the digital revolution is reshaping medical industries at an unprecedented pace,and traditional Chinese medicine(TCM)is no exception[1-4].The paper“From digits towards digitization:the past,present,and future of traditional Chinese medicine”by Academician&TCM National Master Qi WANG(王琦).
基金supported by grants from the Natural Science Foundation of Shandong Province(Grant No.ZR2024QH058).
文摘In the era of precision medicine,the breast cancer surgical treatment field is gradually moving toward a de-escalation model.Through precise preoperative assessments and multidisciplinary decision-making,surgical trauma can be decreased,and patients’quality of life can be improved by ensuring safety.Herein,we explore the axillary de-escalation surgery model for breast cancer.
文摘Lynch syndrome(LS)is the most common hereditary colorectal cancer(CRC)predisposition syndrome,characterized by a high mutational burden and microsatellite instability-high(MSI-H)tumors.Immunology of LS-associated CRC(LS-CRC)is unique,with significant implications for treatment.Despite well-established knowledge of LS immunology,immunotherapy dose and treatment response can vary significantly based on local tumor immunity and specific germline pathogenic variant of LS genes.This variability necessitates tailored surveillance strategies and new personalised immunotherapy approaches for LS patients.LS-CRC often benefits from immunotherapy due to the distinct tumor microenvironment(TME)and the variety of tumor infiltrating lymphocytes(TILs).This perspective discusses a novel approach of analysing spatial TILs at a single-cell level using tumor whole slide images(WSIs)that accounts for the distinct TME of LS-CRC.By emphasizing the necessity of personalized medicine in hereditary cancer syndromes,the future research and clinical practices that enhance patient outcomes through precision oncology is inspired.
基金supported by grants from the National Natural Science Foundation of China(Grant Nos.82103614 and 32171363)Natural Science Foundation of Fujian Province of China(Grant No.2021J05007)+4 种基金funding from the start-up fund for Fujian Key Laboratory of Precision Diagnosis and Treatment in Breast CancerXiamen’s Key Laboratory of Precision Medicine for Endocrine-Related Cancersstart-up and supporting funds from the Third Affiliated Hospital of Kunming Medical University,Yunnan Cancer Hospital for Guo-Jun Zhang and Jing-Wen BaiKey Research and development program for social development of Yunnan Science and Technology Department(Grant No.202403AC100014-2)horizontal project funding from the Third Affiliated Hospital of Kunming Medical University(Grant Nos.20233160A0866 and 20243160A0511)。
文摘The management of breast cancer,one of the most common and heterogeneous malignancies,has transformed with the advent of precision medicine.This review explores current developments in genetic profiling,molecular diagnostics,and targeted therapies that have revolutionized breast cancer treatment.Key innovations,such as cyclin-dependent kinases 4/6(CDK4/6)inhibitors,antibodydrug conjugates(ADCs),and immune checkpoint inhibitors(ICIs),have improved outcomes for hormone receptor-positive(HR+),HER2-positive(HER2+),and triple-negative breast cancer(TNBC)subtypes remarkably.Additionally,emerging treatments,such as PI3K inhibitors,poly(ADP-ribose)polymerase(PARP)inhibitors,and m RNA-based therapies,offer new avenues for targeting specific genetic mutations and improving treatment response,particularly in difficult-to-treat breast cancer subtypes.The integration of liquid biopsy technologies provides a non-invasive approach for real-time monitoring of tumor evolution and treatment response,thus enabling dynamic adjustments to therapy.Molecular imaging and artificial intelligence(AI)are increasingly crucial in enhancing diagnostic precision,personalizing treatment plans,and predicting therapeutic outcomes.As precision medicine continues to evolve,it has the potential to significantly improve survival rates,decrease recurrence,and enhance quality of life for patients with breast cancer.By combining cutting-edge diagnostics,personalized therapies,and emerging treatments,precision medicine can transform breast cancer care by offering more effective,individualized,and less invasive treatment options.
基金Supported by the Natural Science Foundation of Jilin Province,No.YDZJ202401182ZYTSJilin Provincial Key Laboratory of Precision Infectious Diseases,No.20200601011JCJilin Provincial Engineering Laboratory of Precision Prevention and Control for Common Diseases,Jilin Province Development and Reform Commission,No.2022C036.
文摘Artificial intelligence(AI)is driving a paradigm shift in gastroenterology and hepa-tology by delivering cutting-edge tools for disease screening,diagnosis,treatment,and prognostic management.Through deep learning,radiomics,and multimodal data integration,AI has achieved diagnostic parity with expert cli-nicians in endoscopic image analysis(e.g.,early gastric cancer detection,colorectal polyp identification)and non-invasive assessment of liver pathologies(e.g.,fibrosis staging,fatty liver typing)while demonstrating utility in personalized care scenarios such as predicting hepatocellular carcinoma recurrence and opti-mizing inflammatory bowel disease treatment responses.Despite these advance-ments challenges persist including limited model generalization due to frag-mented datasets,algorithmic limitations in rare conditions(e.g.,pediatric liver diseases)caused by insufficient training data,and unresolved ethical issues related to bias,accountability,and patient privacy.Mitigation strategies involve constructing standardized multicenter databases,validating AI tools through prospective trials,leveraging federated learning to address data scarcity,and de-veloping interpretable systems(e.g.,attention heatmap visualization)to enhance clinical trust.Integrating generative AI,digital twin technologies,and establishing unified ethical/regulatory frameworks will accelerate AI adoption in primary care and foster equitable healthcare access while interdisciplinary collaboration and evidence-based implementation remain critical for realizing AI’s potential to redefine precision care for digestive disorders,improve global health outcomes,and reshape healthcare equity.
基金supported by the Chinese Academy of Medical Sciences(Grant No.2021RU002)Beijing Natural Science Foundation(Grant No.Z240013)+2 种基金National Natural Science Foundation of China(Grant Nos.82450111,82388102,82373416,and 92259303)Beijing Research Ward Excellence Program(Grant Nos.BRWEP2024W034080200 and BRWEP2024W034080204)Peking University People’s Hospital Research and Development Funds(Grant No.RZG2024-02).
文摘Organoids are three-dimensional stem cell-derived models that offer a more physiologically relevant representation of tumor biology compared to traditional two-dimensional cell cultures or animal models.Organoids preserve the complex tissue architecture and cellular diversity of human cancers,enabling more accurate predictions of tumor growth,metastasis,and drug responses.Integration with microfluidic platforms,such as organ-on-a-chip systems,further enhances the ability to model tumor-environment interactions in real-time.Organoids facilitate in-depth exploration of tumor heterogeneity,molecular mechanisms,and the development of personalized treatment strategies when coupled with multi-omics technologies.Organoids provide a platform for investigating tumor-immune cell interactions,which aid in the design and testing of immune-based therapies and vaccines.Taken together,these features position organoids as a transformative tool in advancing cancer research and precision medicine.
文摘Artificial intelligence(AI)and machine learning(ML)are transforming spine care by addressing diagnostics,treatment planning,and rehabilitation challenges.This study highlights advancements in precision medicine for spinal pathologies,leveraging AI and ML to enhance diagnostic accuracy through deep learning algorithms,enabling faster and more accurate detection of abnormalities.AIpowered robotics and surgical navigation systems improve implant placement precision and reduce complications in complex spine surgeries.Wearable devices and virtual platforms,designed with AI,offer personalized,adaptive therapies that improve treatment adherence and recovery outcomes.AI also enables preventive interventions by assessing spine condition risks early.Despite progress,challenges remain,including limited healthcare datasets,algorithmic biases,ethical concerns,and integration into existing systems.Interdisciplinary collaboration and explainable AI frameworks are essential to unlock AI’s full potential in spine care.Future developments include multimodal AI systems integrating imaging,clinical,and genetic data for holistic treatment approaches.AI and ML promise significant improvements in diagnostic accuracy,treatment personalization,service accessibility,and cost efficiency,paving the way for more streamlined and effective spine care,ultimately enhancing patient outcomes.
基金Projects(U22B2084,52275483,52075142)supported by the National Natural Science Foundation of ChinaProject(2023ZY01050)supported by the Ministry of Industry and Information Technology High Quality Development,China。
文摘The gears of new energy vehicles are required to withstand higher rotational speeds and greater loads,which puts forward higher precision essentials for gear manufacturing.However,machining process parameters can cause changes in cutting force/heat,resulting in affecting gear machining precision.Therefore,this paper studies the effect of different process parameters on gear machining precision.A multi-objective optimization model is established for the relationship between process parameters and tooth surface deviations,tooth profile deviations,and tooth lead deviations through the cutting speed,feed rate,and cutting depth of the worm wheel gear grinding machine.The response surface method(RSM)is used for experimental design,and the corresponding experimental results and optimal process parameters are obtained.Subsequently,gray relational analysis-principal component analysis(GRA-PCA),particle swarm optimization(PSO),and genetic algorithm-particle swarm optimization(GA-PSO)methods are used to analyze the experimental results and obtain different optimal process parameters.The results show that optimal process parameters obtained by the GRA-PCA,PSO,and GA-PSO methods improve the gear machining precision.Moreover,the gear machining precision obtained by GA-PSO is superior to other methods.
基金funded by the Tianfu Emei Plan(a talent program of Sichuan Province,China),awarded to Huilian Che。
文摘Approximately 2.5%of the global population experience allergic reactions to seafood,making it one of the most prevalent and life-threatening allergies.Seafood allergy can lead to the disruption of the intestinal barrier,possibly due to aberrant intestinal glycosylation.In this study,the mechanisms underlying seafood allergy were explored through the lens of intestinal glycobiology.Mice were sensitized with tropomyosin,resulting in significant increases in allergy symptom scores,specific antibody and T helper 2 cytokine levels.Intestinal damage was confirmed by histopathology,as well as by assessments and levels of diamine oxidase and claudin-1.Moreover,alterations in glycosylated proteins within the jejunum were analyzed using highthroughput mass spectrometry and the pGlyco3.0 search engine.Precision N-glycoproteomics analysis yielded 2283 glycosylation peptides corresponding to 655 unique glycosylation sites on 399 proteins.Differential expression and enrichment analyses revealed that differentially expressed glycoproteins were significantly enriched in the extracellular matrix(ECM)-receptor interaction pathway and focal adhesion pathway.In conclusion,tropomyosin sensitization leads to intestinal glycome changes,accompanied by remodeling of the intestinal ECM.Our research establishes an essential theoretical basis for targeting the intestinal glycome and ECM remodeling in a precise and fine-tuned manner for the treatment of food allergies.
文摘Background:Precision medicine(PM)has taken center stage in healthcare since the completion of the genomic project.Developed countries have gradually integrated PM into mainstream patient management.However,Nigeria still grapples with wide acceptance,key translational research and implementation of PM.This study sought to explore the knowledge and attitude of PM among pharmacists as key stakeholders in the healthcare team.Methods:A cross‐sectional study was conducted in selected tertiary hospitals across the country.A 21‐item semi‐structured questionnaire was administered by hybrid online and physical methods and the results analyzed with Statistical Package for the Social Sciences Version 25.Descriptive statistics were used to summarize the data.A chi‐square test was employed to determine the association of knowledge of PM and the sociodemographic characteristics of the study population.Results:A total of 167 hospital pharmacists participated in the study.A high proportion of the participants are familiar with artificial intelligence(91.75%),Pharmacogenomics(84.5%),and precision medicine(61%).Overall,38.9%of the pharmacists had a good knowledge while 13.2%had a poor knowledge of PM and associated terms.The level of knowledge did not correlate significantly with gender(X^(2)=3.21,p=0.201),age(X^(2)=5,p=0.27),marital status(X^(2)=3.21,p=0.201),and professional level(X^(2)=6.85,p=0.144).The most important value of precision medicine to hospital pharmacists is the ability to minimize the impact of disease through preventive medicine(49%)while a large portion are pursuing and or actively planning to pursue additional education in precision medicine.Conclusions:There is a highly positive attitude toward the prospect of PM among hospital pharmacists in Nigeria.Education modules in this field are highly recommended as most do not have a holistic knowledge of terms used in PM.Also,more research aimed at translating PM knowledge into clinical practice is recommended.
文摘Pancreatic ductal adenocarcinoma(PDAC)is a global health challenge and remains one of the most lethal malignancies;there are only a few therapeutic options.However,significant efforts have led to the identification of major genetic factors that drive the progression and pathogenesis of PDAC.Notably,the research and application of molecular targeted therapies and immunotherapies have rapidly increased and facilitated great progress in the treatment of many malignant tumors,additional targeted therapies and immunotherapy based on next-generation sequencing results provide new opportunities for the diagnosis and treatment of pancreatic tumors.Immune checkpoint inhibitors are also now being incorporated as PDAC therapies,and combinations of molecularly targeted therapies with immunotherapies are emerging as strategies for boosting the immune response.The investigation of biomarkers of a response or primary resistance to immunotherapies is also an emerging research area.Herein,we further discuss the recent technological advances that continue to expand our understanding of PDAC complexity.We discuss the advancements expected in the near future,including biomarker-driven treatments and immunotherapies.We presume that the clinical translation of these research efforts will improve the survival outcomes of this challenging disease,which are currently dismal.
基金co-supported by the Enterprise Innovation and Development Joint Program of the National Natural Science Foundation of China(No.U20B2032)Open Project Funding of State Key Laboratory for High Performance Tools(GXNGJSKL-2024-08)+1 种基金Open Foundation of the State Key Laboratory of Intelligent Manufacturing Equipment and Technology(IMETKF2023005)Introduced Innovative Scientific Research Team Project of Zhongshan(the tenth batch)(CXTD2023008)。
文摘Micro-grinding has been widely used in aerospace and other industry.However,the small diameter of the micro-grinding tool has limited its machining performance and efficiency.In order to solve the above problems,micro-structure has been applied on the micro-grinding tool.A morphology modeling has been established in this study to characterize the surface of microstructured micro-grinding tool,and the grinding performance of micro-structured micro-grinding tool has been analyzed through undeformed chip thickness,abrasive edge width,and effective distance between abrasives.Then deviation analysis,path optimization and parameter optimization of microchannel array precision grinding have been finished to improve processing quality and efficiency,and the deflection angle has the most obvious effects on the rectangular slot depth,micro-structured micro-grinding tool could reduce 10%surface roughness and 20%grinding force compared to original micro-grinding tool.Finally,the microchannel array has been machined with a size deviation of 2μm and surface roughness of 0.2μm.
文摘With the rapid development of artificial intelligence(AI)technology,multimodal data integration has become an important means to improve the accuracy of diagnosis and treatment in gastroenterology and hepatology.This article systematically reviews the latest progress of multimodal AI technology in the diagnosis,treatment,and decision-making for gastrointestinal tumors,functional gastrointestinal diseases,and liver diseases,focusing on the innovative applications of endoscopic image AI,pathological section AI,multi-omics data fusion models,and wearable devices combined with natural language processing.Multimodal AI can significantly improve the accuracy of early diagnosis and the efficiency of individualized treatment planning by integrating imaging,pathological data,molecular,and clinical phenotypic data.However,current AI technologies still face challenges such as insufficient data standardization,limited generalization of models,and ethical compliance.This paper proposes solutions,such as the establishment of cross-center data sharing platform,the development of federated learning framework,and the formulation of ethical norms,and looks forward to the application prospect of multimodal large-scale models in the disease management process.This review provides theoretical basis and practical guidance for promoting the clinical translation of AI technology in the field of gastroenterology and hepatology.
基金Supported by the National Natural Science Foundation of China,No.82273457the Natural Science Foundation of Guangdong Province,No.2023A1515012762Science and Technology Special Project of Guangdong Province,No.210715216902829.
文摘Colorectal cancer(CRC)ranks as the third most common cancer globally and the second leading cause of cancer-related deaths,representing a significant health burden.Despite advancements in traditional treatments such as surgery,chemotherapy,targeted therapy,and immunotherapy,these approaches still face challenges,including high costs,limited efficacy,and drug resistance.Drug repurposing has emerged as a promising strategy for CRC treatment,offering advantages with reduced development timelines,lower costs,and improved drug accessibility.This review explores drug repurposing strategies for CRC,supported by multidisciplinary technologies,and discusses the current challenges in the field.
文摘The increasing use of UAV-based LiDAR systems for high-resolution mapping highlights the need for reliable,field-validated accuracy assessment methods.This study presents a practical technique for evaluating geometric and radiometric performance using georeferenced,high-reflectivity foil targets.The method enables precise extraction of target centers and correction of systematic georeferencing errors through 3D transformation.The approach was applied at the Tora Cement Factory in Cairo,Egypt—an industrial site with complex topography—using a DJI Matrice 300 RTK UAV equipped with the Zenmuse L1 LiDAR sensor and Zenmuse P1 photogrammetric camera.Three test flights were performed at altitudes of 50 m(nadir and oblique)and 70 m(oblique),with a high-resolution Structure-from-Motion(SfM)point cloud generated for reference.After transformation,the global RMSE of the LiDAR dataset was reduced to approximately 2.8∼3.2 cm,improving upon the raw uncorrected accuracy of up to 4.6 cm.Surface-wise comparisons showed RMSEs of 3.1 cm on flat areas,3.8 cm on rugged terrain,and 4.5 cm on vertical structures.Additionally,the RGB data embedded in the LiDAR point cloud exhibited a systematic spatial offset between 18 and 43 cm,with an average internal standard deviation near 5 cm,indicating a potential limitation for radiometric applications.The proposed method offers a cost-effective,accurate,and repeatable solution for UAV LiDAR validation and supports operational deployment,quality assurance,and system calibration in real-world scenarios.
基金Supported by National Key Research and Development Program of China(Grant No.2022YFB3304200)National Natural Science Foundation of China(Grant No.52205288)+1 种基金China Postdoctoral Science Foundation(Grant Nos.2024T170795,2024M762815)Zhejiang Provincial Key Research and Development Program(Grant No.2024C01029)。
文摘Assembly precision greatly influences the performance of complex high-end equipment.The traditional industrial assembly process and deviation transfer are implicit and uncertain,causing problems like poor component fit and hard-to-trace assembly stress concentration.Assemblers can only check whether the dimensional tolerance of the component design is exceeded step by step in combination with prior knowledge.Inversion in industrial assembly optimizes assembly and design by comparing real and theoretical results and doing inversion analysis to reduce assembly deviation.The digital twin(DT)technology visualizes and predicts the assembly process by mapping real and virtual model parameters and states simultaneously,expanding parameter range for inversion analysis and improving inversion result accuracy.Problems in improving industrial assembly precision and the significance and research status of DT-driven parametric inversion of assembly tools,processes and object precision are summarized.It analyzes vital technologies for assembly precision inversion such as multi-attribute assembly process parameter sensing,virtual modeling of high-fidelity assembly systems,twin synchronization of assembly process data models,multi-physical field simulation,and performance twin model construction of the assembly process.Combined with human-cyber-physical system,augmented reality,and generative intelligence,the outlook of DT-driven assembly precision inversion is proposed,providing support for DT's use in industrial assembly and precision improvement.
基金supported by the National Natural Science Foundation of China(Nos.82272847,82304417,82303529,82171333)China Postdoctoral Science Foundation(Nos.2023TQ0307,2023M743231,2023M730971)+2 种基金Science and Technology Project of Henan Province(No.242102311204)Postdoctoral Fellowship Program of CPSF(No.GZB20230675)Modern Analysis and Computer Center of Zhengzhou University.
文摘Colon-targeted oral drug delivery systems are one of the most promising therapeutic strategies for alleviating and curing inflammatory bowel disease(IBD),but they still face challenges in successfully passing through the harsh gastrointestinal environment and intestinal mucus barrier.To overcome the gastrointestinal barriers for oral drug delivery mentioned above,a“spore-like”oral nanodrug delivery platform(Cur/COS/SC NPs)has been developed.Firstly,chitooligosaccharides(COS)are encapsulated on the surface of Curcumin nanoparticles(Cur NPs)to form carrier-free nanoparticles(Cur/COS NPs).Subsequently,inspired by the natural high resistance of spore coat(SC),SC is chosen as the“protective umbrella”to encapsulate Cur/COS NPs for precision targeted therapy of IBD.After oral administration,SC can effectively protect NPs through the rugged gastrointestinal environment and exhibit excellent intestinal mucus penetration characteristics.Moreover,the negatively-charged Cur/COS/SC NPs specifically target positivelycharged inflamed colon via electrostatic interactions.It is demonstrated that Cur/COS/SC NPs can promote the expression of tight junction proteins,inhibit aberrant activation of the Toll-like receptor 4/myeloid differentiation primary response gene 88/nuclear factor-κB(TLR4/MyD88/NF-κB)signaling pathway,and downregulate the levels of pro-inflammatory factors,exhibiting excellent anti-inflammatory effects.Notably,it is found that Cur/COS/SC NPs can significantly increase the richness and diversity of gut microbiota,and restore the homeostasis of gut microbiota by inhibiting pathogenic bacteria and promoting probiotics.Hence,Cur/COS/SC NPs provide a safe,efficient,and feasible new strategy for IBD treatment.
